| Among microwave power sources,magnetron has the characteristics of small structure,high efficiency and low cost.It is widely used in daily life,such as household microwave oven.With the development of computer technology artificial intelligence recognition technology,the design of intelligent products has caused extensive research.In view of the problems such as too many buttons on the selection interface of household microwave ovens and complex operation,the demand for artificial intelligence microwave ovens is gradually increasing.In order to realize intelligent recognition of the type of heated food and simplify the operation process of microwave oven,this paper designs the intelligent food recognition system based on the magnetron of domestic microwave oven from the hardware part and the software part respectively.The main work contents include the following:1.Investigate the background and research status of microwave technology,artificial intelligence identification technology and artificial intelligence microwave oven,and get the design ideas.The basic theories of magnetron,artificial intelligence recognition technology and AI magnetron related technology are introduced.Get the support of the design from the theoretical analysis,improve the feasibility of the design.2.Design an intelligent food recognition system based on the magnetron of household microwave oven,introduce the basis of system design and the selection of characteristic parameters,and use CST computer software to simulate and analyze the vibration characteristics of microwave output signals of household microwave oven magnetron.The system design includes the software technology part of the hardware part.The hardware part is mainly the design of the synthetic power source.The software technology part mainly includes: the feature parameter acquisition and recognition technology,such as phase feature detection technology.Data processing methods for characteristic parameters,such as big data analysis.Set up an experiment to verify the feasibility of intelligent identification of food systems,and conduct a large number of measurements and collection of characteristic parameter data from five categories to obtain more comprehensive data and improve the success rate of the experiment and the reliability of the experimental data.3.Conduct experiments to verify the feasibility of the system.Data were measured and collected from five categories.After the experiment,the characteristic data of microwave signal were analyzed,and the rule of microwave signal amplitude reflected by different foods was obtained.Under the conditions of this experiment,the reflected signal amplitude of 1000 g water,cabbage and pork fluctuated around 715.3mV,292.5m and 353.4mV respectively.The law of reflected signal amplitude of different weights of milk: 50 g milk reflected signal amplitude of 868 mV,300 g milk reflected signal amplitude of 404.6mV,between 50 g and 300 g,with the increase of milk weight,the reflected signal amplitude decreases.The computer system realizes the function of identifying food type and weight by comparing the detected amplitude rule with the data in the database.The subsequent recognition rate can be improved by database expansion.4.Data analysis of the vibration characteristics of microwave signals shows that different types of food have different vibration characteristics.Under the experimental conditions,the vibration time rule: water,cabbage and pork are 360 ns,320ns and 180 ns,respectively.Amplitude law of the whole stage of starting vibration: water,cabbage and pork float around 121.3mV,28.2mV and 54.3mV respectively.Based on these rules,the function of food type recognition is preliminarily realized,which verifies the feasibility of intelligent recognition system.These experiments and data also lay a foundation for the establishment of database and the design of artificial intelligence microwave oven. |
